Non-traditional Security: A Risk-Centric View

As described in Saha and Chakrabarti (South Asian Survey 28(1):111-132, 2021: 112), "COVID-19 has firmly established itself as the single largest security disrupter of this century in the non-traditional sense. It has necessitated a recalibration of securitisation framework.…" The impact of the COVID-19 pandemic certainly illustrates the transnational nature of today's security landscape. Similarly, events such as the WannaCry cyber-attack, global terrorism, serious and organized crime, disease vectors, and natural disasters create challenges that affect both global and national security interests. Such events are shaping the security calculus across dimensions such as health security, economic security, food security, and energy security emerging as interrelated concepts that characterize the security landscape as complex. The increased transnational flow of people, goods, money, and information as products of "globalization” has also changed the security landscape in terms of the "globalization” of risks. This transnational/transborder nature of security challenges our traditional views of national security characterized by state-based, military dimensions. The non-traditional security calculus thereby emerges as part of the security landscape that can often have significant national security impacts through the implications associated with systemic risks. Outstanding scholarly work has been presented on the topic of non-traditional security through the lens of International Relations and Contemporary Security Studies (e.g., see Collins, Contemporary security studies. Oxford University Press, Oxford, 2013). This chapter presents non-traditional security through a risk-centric lens and explores the notion of systemic risk as part of the security calculus. COVID-19 will be used as an illustrative example of a shock to societal systems that reveals systemic risks, vulnerabilities, and impacts across the non-traditional security domains. © Springer Nature Switzerland AG 2022.

Do lower environmental, social, and governance (ESG) rated companies have higher systemic impact? Empirical evidence from Europe and the United States

In recent years, companies have increasingly been characterized by environmental, social, and governance (ESG) scores, and investors and academics have raised questions concerning financial performance and investment risks. Now, as the European Banking Authority has acknowledged that ESG risks can potentially impact the economic and financial system, the debate on systemic risk has gained traction. Understanding the relationship between ESG merit and systemic risk is of utmost importance for the stability of the economic and financial system, still, research is limited. Relying on real‐world European and United Stated data, we quantify systemic risk by means of QL‐CoVaR. Empirical analyses of the entire period from 2007 to 2021 show that companies with high ESG scores tend to exhibit low QL‐CoVaR values indicating a positive effect of ESG scores. Such evidence is confirmed by clustering the individual companies into ESG portfolios and focusing on COVID‐19. Additional insights using the individual pillars are also provided.

Reinsuring pandemics: the role of government and public-private partnerships between reinsurers and governments.

Pandemic-related business interruption (BI) losses are generally considered 'uninsurable' because, in order to pool sufficient premium revenue to meet valid claims, premiums would be unaffordable for the majority of policyholders. This paper explores whether and how such losses might be made insurable in the U.K. The authors consider post-pandemic governmental responses, including the role of the Financial Conduct Authority (FCA) and the meaning and implications of FCA v Arch Insurance (U.K.) Ltd ([2021] UKSC 1). The central premise of the paper is to highlight the importance of reinsurance in increasing an underwriter's insuring capacity and to illustrate how, with the support of government in the form of a public-private partnership (PPP), 'uninsurable' risks of this type may be made insurable. The authors propose a PPP, 'Pandemic Business Interruption Re', which provides, in their view, a feasible and defensible solution that would confer the benefit of increasing policyholders' faith in the industry's ability to underwrite pandemic-related BI claims and reduce reliance on ex post government aid.

The systemic risk of US oil and natural gas companies

We analyse the evolution of the systemic risk impact of oil and natural gas companies since 2000. This period is characterised by several events that affected energy source markets: the real effect of the global financial crisis, the explosion of shale production and the diffusion of the Covid-19 pandemic. The price of oil and natural gas showed extreme swings, impacting companies' financial situations, which, accompanied by technological developments in shale production, had an impact on the debt issuance and on the overall risk level of the oil and natural gas sector. By studying the systemic impact of oil and natural gas companies on risk in the financial market, measured by the ΔCoVaR, we observe that in the most recent decade, their role is sensibly increasing compared to 2000–2010, even accounting for the possible effect associated with the increase in companies' sizes. In addition, our results show evidence of a decreasing relevance of traditional drivers of systemic risk, suggesting that additional factors might be present. Finally, when focusing on the impact of Covid-19, we document its relevant role in fuelling the increase in the oil and natural gas companies' systemic impact. © 2023 The Authors

Research on Financial Systemic Risk Assessment Algorithm Based on Risk Data Fuzzy Cluster Analysis

The financial industry is a high-risk industry. Once the financial industry risk happen, it will affect the economic development. Ensuring the safe, efficient and steady operation of finance and preventing systemic financial risks are the urgent needs of China's opening up to the outside world and building a well-off society in an all-round way. Stable and efficient economic development is the basis of financial risk prevention and control, which is the inherent requirement of high-quality economic development. Strengthening macro-prudential management has become the core content of financial regulatory reform in major international organizations and economies after the international coronavirus outbreak and preventing systemic financial risks is the fundamental goal of macro-prudential management. This paper takes the assessment and monitoring of China's systemic financial risks as the research object, and proposes an assessment algorithm of systemic financial risks based on risk data fuzzy clustering analysis. The established financial systemic risk measurement method can identify risks to a certain extent, deeply understand the nature, root and key areas of systemic financial risks, and build a long-term mechanism to prevent and resolve systemic financial risks. © 2022 IEEE.

Could volatile cryptocurrency stimulate systemic risks in the energy sector? Evidence from novel connectedness models

By identifying the connectedness of seven indicators from January 1, 2019, to June 13, 2022, we choose an extended joint connectedness approach to a vector autoregression model with time-varying parameter (TVP-VAR) to analyze interlinkages between Crypto Volatility (CV) and Energy Volatility (EV). Our findings show that the COVID-19 outbreak seems to have an impact on the dynamic connectedness of the whole system, which peaks at about 60% toward the end of 2019. According to net total directional connectedness over a quantile, throughout the 2020–2022 timeframe, natural gas and crude oil are net shock transmitters, while the CV, clean energy, solar energy, and green bonds consistently receive all other indicators. Specifically, pairwise connectedness indicates that the CV appears to be a net transmitter of shocks to all energy indicators before the COVID-19 outbreak but acts as a net receiver of shocks from clean energy, wind energy, and green bonds in late 2020. The CV mostly has spillover effects on green bonds. The primary net transmitter of shocks to the Crypto market is crude oil. Our findings are critical in helping investors and authorities design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Stochastic ordering of systemic risk in commodity markets

The contribution of commodity risks to the systemic risk is assessed in this paper through a novel approach that relies on the stochastic property of concordance ordering of CoVaR. Considering the period that spans from 2005 to 2022 and the VIX as the proxy for the stability of the financial system, we build the stochastic ordering of systemic risk for 35 commodities belonging to four sectors: Agriculture, Energy, Industrial Metals, and Precious Metals. The estimates of the ΔCoVaR signal that contagion effects from commodity markets to the financial system have been stronger during the years 2017–2019. Backtests validate CoVaR as a more resilient risk measure than the VaR, especially during periods of market turmoils. The stochastic ordering of CoVaR shows that severe losses (downside risk) in commodity markets tend to exacerbate systemic financial distress more than gains (upside risk). Commodity risks arising from WTI and EUA are threatening triggers for systemic risk. In contrast, the financial system is less vulnerable to a broader range of scenarios arising from fluctuations in Gold prices. As top contributors to the systemic risk, among the sectors we find Energy and Precious Metals with respect to upside risk and downside risk. The Covid-19 crisis has deeply amplified the systemic influence arising from the downside risk of WTI, Gasoline, and Natural Gas UK and has confirmed the safe-haven role of Gold. © 2022 Elsevier B.V.

Crises social sensing: longitudinal monitoring of social perceptions of systemic risk during public health crisis

Monitoring how different people–as ‘social sensors'–evaluate and respond to crisis such as pandemics, allows tailoring crisis communication to the social perceptions of the situation, at different moments. To gather such evidence, we proposed a index of social perceptions of systemic risk (SPSR), as an indicator of a situational threat compromising risks to physical health, psychological health, the economy, social relations, health system, and others. This indicator was the core of a social sensing approach applied to crisis situations, implemented during the COVID-19 pandemic through a content analysis of more than 130.000 public comments from Facebook™ users, in COVID-19 related publications. This content coding allowed creating a SPSR index monitored during a one-year descriptive longitudinal analysis. This index correlated with co-occurring events within the social system, namely epidemiological indicators across measurement cycles (e.g. new deaths;cumulative number of infection cases;Intensive Care Unit hospitalizations) and tended to reflect the epidemiological situation severity (e.g. with the highest level registered during the worst pandemic wave). However, discrepancies also occurred, with high SPSR registered in a low severity situation, i.e. low number of hospitalizations and deaths (e.g. school year beginning), or low SPSR in a high severity situation (e.g. 2nd pandemic wave during Christmas), showing other factors beyond the epidemiological situation contributing to the social perceptions. After each ‘crisis period' with SPSR peaking, there was a ‘restoration period', consistently decreasing towards average levels of the previous measurement cycle. This can either indicate social resilience (recovery and resources potentiation) or risk attenuation after a high-severity period. This study serves as preliminary proof of concept of a crises social sensing approach, enabling monitoring of social system dynamics for various crisis types, such as health crisis or the climate crisis. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Tourist Trajectory Prediction Based on Improved LightGBM

Considering the influences of the COVID-19 disease, systemic risks with respect to the tourism industry and the erratic preferences of the tourists have fiercely affected the performance of machine learning models for tourist trajectory prediction. This paper introduces a noise-reduced and Bayesian optimized light gradient boosting machine(LightGBM) to forecast the likelihood of visitors entering the consequent scenic attraction, accommodating to the variability of tourism attributes. The empirical evidence of tourism data in Luoyang City Hall from March 2020 to November 2021 illustrates that our practice surpasses the baseline LightGBM mechanism as well as a random search-based technique regarding prediction loss by 5.39% and 4.42% correspondingly. The proposed research demonstrates a promising stride in the improvement of intelligent tourism in the experimental area by enhancing tourist experiences and allocating tourism resources efficiently, which can also be smoothly applied to other scenic spots. © 2023 SPIE.

Do lower environmental, social, and governance (ESG) rated companies have higher systemic impact? Empirical evidence from Europe and the United States

In recent years, companies have increasingly been characterized by environmental, social, and governance (ESG) scores, and investors and academics have raised questions concerning financial performance and investment risks. Now, as the European Banking Authority has acknowledged that ESG risks can potentially impact the economic and financial system, the debate on systemic risk has gained traction. Understanding the relationship between ESG merit and systemic risk is of utmost importance for the stability of the economic and financial system, still, research is limited. Relying on real-world European and United Stated data, we quantify systemic risk by means of QL-CoVaR. Empirical analyses of the entire period from 2007 to 2021 show that companies with high ESG scores tend to exhibit low QL-CoVaR values indicating a positive effect of ESG scores. Such evidence is confirmed by clustering the individual companies into ESG portfolios and focusing on COVID-19. Additional insights using the individual pillars are also provided.

National perspectives of COVID-19: case of Sri Lanka

COVID-19 pandemic has given insights into the systemic risks of a hazard, demonstrating the potency of biological hazards to not only render one sector dysfunctional but also fail the entire system. The grave and devastating impacts of the current COVID-19 call for the need to assess the state of global and national preparedness for future pandemics. This chapter provides an outline of Sri Lanka's response to the COVID-19 pandemic while delving into the current status and gaps concerning preparedness for pandemics in the country. The analysis is aimed at providing key recommendations for policymakers to improve national-level preparedness for anticipated pandemic threats. This chapter has drawn on a review of secondary literature and primary data gathered through in-depth interviews conducted with key informants in the disaster management and public health sectors in the country. Findings show that while preparedness planning for biological hazards is predominantly a responsibility of the health sector in the country, there is a pressing need to strengthen such preparedness through a unified legal framework and system of governance that allow for the transfer of relevant expertise, infrastructure, and lessons learned from previous hazards contexts to situations of pandemics;the incorporation of pandemic preparedness into national-level DRR efforts and subnational-level DRR planning;intensifying national focus on building economic and social resilience;emulating a multisectoral approach, enhancing private sector participation, and establishing a national framework to foster preparedness for parallel hazards. © 2022 Elsevier Inc. All rights reserved.

Cryptocurrency Bubble on the Systemic Risk in Global Energy Companies

Financialization has brought new challenges to the international energy markets, making energy systemic risk a more complicated issue. One of the important fea-tures is the development of cryptocurrency, which has become a critical part of the global financial markets. As a consequence, the rise and fall of cryptocurrency can have nonnegligible impacts on the systemic risks in the international energy sec-tor. This paper empirically tests this hypothesis using the equity data of the top 100 energy companies from 2014 to 2021. Specifically, we explore the extreme shocks of cryptocurrency using multiple bubble tests, and then we test to what extent bubbles in cryptocurrency markets can affect systemic risk in the energy sector. Our empirical results show that the formation of cryptocurrency bubbles, especially when the bubbles burst, significantly increases systemic risks in the energy sector. This effect retains the same in the recent COVID-19 pandemic period. In addition, oil and gas companies play an essential channel in the risk spillover from crypto-currency markets to the international energy markets. © 2022 by the IAEE. All rights reserved.

Data Mining for Predicting and Finding Factors of Bankruptcy

The financial crisis, since the pandemic outbreak due to COVID-19, the dissemination and invasive systemic risk in the global financial environment have drawn the attention to organizations' solvency monitoring methods. Inevitably, in this paper we have looked at the both bankruptcy prediction and the factors that lead to bankruptcy. The dataset for this study was acquired from Kaggle, which was based on the Taiwan Economic Journal, from 1999 to 2009. The corporate statutes of the Taiwan Stock Exchange were utilized to determine a company's bankruptcy. It was a highly imbalanced dataset having 220 Non-bankrupt and 6,599 bankrupt data. We have used Random Forest, Support Vector Machine, Artificial Neural Network, XGBoost, and LightGBM classifiers regarding bankruptcy prediction. On the other hand, to find the factors that lead to bankruptcy, we did an empiric analysis for which we calculated fourteen statistical values of both bankrupted and non-bankrupted features and saw their cosine similarities. These factors will help any financial company to plan its financial ratios for preventing bankruptcy. Here we got the best performance from the Artificial Neural Network with 98.64% accuracy. And we found four factors that were responsible for the bankruptcy in our dataset. Here, the factors determining bankruptcy are crucial because by finding these factors and the likelihood of bankruptcy, companies can take the necessary steps to plan their financial ratios and ensure the solvency of their businesses. © 2022 IEEE.

Economic resilience in an era of ‘systemic risk’: Insights from four key economic sectors in Sri Lanka

COVID-19 has showcased the systematic nature of risks. Its effects have spanned beyond the health sector causing severe economic disruptions. Sri Lanka's GDP contracted by 3.6% in 2020 from a 2.3% growth in 2019, reflecting the largest economic downturn recorded in the country's history. Although the COVID-19 pandemic has been largely perceived as unprecedented by most economic sectors and businesses functioning within them, pandemics are not a novel phenomenon given their intermittent occurrence in the past. This study aimed at examining the resilience of four key sectors in Sri Lanka during the COVID-19 pandemic, namely apparel, tourism, agriculture and construction. The study sought to identify the factors that have both enhanced and hindered their resilience during the pandemic and provide recommendations to strengthen their resilience for future pandemics and multi-hazard scenarios featuring pandemics. The study draws upon primary data gathered through four round table discussions carried out with a total of 31 key informants representing the selected sectors. The findings reveal that for economic resilience to be achieved within the selected economic sectors, resilience building measures should be undertaken at three levels, while also recognising the need for consonance and congruence between measures taken at each level: 1) organizational level;2) sectoral level and 3) country level.

Insights from the COVID-19 Pandemic for Systemic Risk Assessment and Management

The COVID-19 pandemic has activated hundreds of interdependent long-lasting risks across all sectors of society. Zoonotic diseases are on the rise, fuelled by climatic change, by encroachment and destruction of habitats, and by unsustainable practices. Risk assessment and management must be greatly improved to prevent even worse consequences than COVID-19 if the next pandemic is caused by an agent with higher infectiousness and lethality. Insights from a project on systemic pandemic risk management reveal that the interdependency of risks creates cascading effects mediated by millions of vicious cycles which must be addressed to gain control over a pandemic. We propose a method for systemic, cross-sectoral risk assessment that detects the myriad of causal influences resulting from the risks, allowing to identify and mitigate the most potent risks, i.e., those participating in the highest numbers of vicious loops. © 2022, IFIP International Federation for Information Processing.

Study on the Risk Contagion Effect between Chinese and American Financial Markets Based on BEKK-GARCH Model

With the significant increase of uncertainties facing the global economy, systemic risks in China and international financial markets occur frequently, seriously restricting the stable development of financial markets and the smooth operation of the economy. In the context of economic globalization and the integration of market economy, the increased correlation between markets leads to the enhancement of risk resonance effect, which leads to the contagion of risks among different markets, among which China is particularly affected by the fluctuation effect of American market risks. In view of this, this paper uses the BEKK-GARCH (1, 1) model to explore the risk contagion effect between China and the United States during the period of January 2, 2001 solstice and March 19, 2021. The results show that, first, in the full sample interval, there is a two-way volatility spillover effect between the Chinese market and the American market and there is a Granger causality. The degree of volatility spillover from American to China is more significant. Second, in the four crisis intervals, the volatility spillover effects of China and the US show some characteristics different from those of the full sample interval. During the European debt crisis, there was a positive volatility spillover effect between the two markets, and the spillover degree of systemic risks in China's market to the US market was more significant. During COVID-19, the US market risks had negative volatility spillover to the Chinese market. Third, both the Chinese and American markets are affected by their own fluctuations in the early stage with relatively large impacts and short duration, while the impact of the US on China lasts for about 7 periods. © 2021 IEEE.

Does the source of oil price shocks matter for the systemic risk?

This paper investigates the impact of different oil price shocks on systemic risk under different market conditions. We show that the negative impact of negative oil price shocks on systemic risk is greater than the positive impact of positive oil price shocks. Systemic risk is always negatively affected by oil-specific demand shocks but positively affected by oil supply shocks when the market is under medium and low systemic risk levels. By testing the effect of crises, we find that the influence of positive and negative oil price shocks on systemic risk was declined due to the COVID-19 pandemic. © 2022 Elsevier B.V.

Elicitation, analysis and mitigation of systemic pandemic risks

The Covid-19 pandemic has disrupted the health care system and affected all sectors of society, including critical infrastructures. In turn, the impact on society's infrastructures has impacted back on the health care sector. These interactions have created a system of associated risks and outcomes, where the outcomes of risks are risks themselves and where the resulting consequences are complex vicious cycles. Traditional risks assessment methods cannot cope with interdependent risks. This paper describes a novel risk systemicity approach to elicit and mitigate the systemic risks of a major pandemic. The approach employed the internet-based software strategyfinder™ in workshops to elicit relevant risk information from sixteen appropriately selected experts from the health care sector and major sectors impacted by and impacting back on the health care sector. The risk information was processed with powerful analytical tools of strategyfinder to allow the experts to prioritise portfolios of strategies attacking the vicious cycles. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.